Advances in Difference-in-Differences in Econometrics {https://t.co/AZrL5Ctsb6} #rstats #DataScience
— R-bloggers (@Rbloggers) September 30, 2021
Machine Learning with R: A Complete Guide to Linear Regression {https://t.co/SQlezk20rc} #rstats #DataScience
— R-bloggers (@Rbloggers) September 27, 2021
How to Remove Outliers in R {https://t.co/IcHI3c7m1U} #rstats #DataScience
— R-bloggers (@Rbloggers) September 29, 2021
A Step-By-Step Guide To Web Scraping With R {https://t.co/hSAl6ImAp2} #rstats #DataScience
— R-bloggers (@Rbloggers) September 25, 2021
Top 10 dplyr Functions — Data Analysis Made Easy {https://t.co/kbrIxGHqLM} #rstats #DataScience
— R-bloggers (@Rbloggers) September 25, 2021
Introduction to Machine Learning with TensorFlow {https://t.co/M4DbPRFNAu} #rstats #DataScience
— R-bloggers (@Rbloggers) September 29, 2021
Introduction to Deep Learning {https://t.co/Y8ITA0u9IR} #rstats #DataScience
— R-bloggers (@Rbloggers) October 1, 2021
PowerBI vs. R Shiny: Two Popular Excel Alternatives Compared {https://t.co/SqgPZYq9cn} #rstats #DataScience
— R-bloggers (@Rbloggers) September 25, 2021
How to Make Stunning Geomaps in R: A Complete Guide with Leaflet {https://t.co/c1qJQlSjwF} #rstats #DataScience
— R-bloggers (@Rbloggers) September 27, 2021
How to Make Impressive Dashboards in Under 10 Minutes with Shiny {https://t.co/4Kf18yPxbA} #rstats #DataScience
— R-bloggers (@Rbloggers) September 28, 2021
A Simple Two-Stage Stochastic Linear Programming using R {https://t.co/9KaDS397p9} #rstats #DataScience
— R-bloggers (@Rbloggers) October 1, 2021
Tableau vs. R Shiny: Which Excel Alternative Is Right For You? {https://t.co/aAHKB8Htq4} #rstats #DataScience
— R-bloggers (@Rbloggers) September 25, 2021
Advances in Difference-in-Differences in Econometrics {https://t.co/AZrL5Ctsb6} #rstats #DataScience
— R-bloggers (@Rbloggers) September 30, 2021
Confidence and prediction intervals explained… (with a Shiny app!) {https://t.co/di0Ii6oAze} #rstats #DataScience
— R-bloggers (@Rbloggers) September 4, 2021
Download recently published book – Learn Data Science with R {https://t.co/SQt1rmWZAL} #rstats #DataScience
— R-bloggers (@Rbloggers) September 14, 2021
Another 9 R books added to BigBookofR {https://t.co/JBy5FDH1eo} #rstats #DataScience
— R-bloggers (@Rbloggers) September 12, 2021
Machine Learning with R: A Complete Guide to Linear Regression {https://t.co/SQlezk20rc} #rstats #DataScience
— R-bloggers (@Rbloggers) September 27, 2021
Basic R : Read so many CSV files {https://t.co/BLH2RqOLEs} #rstats #DataScience
— R-bloggers (@Rbloggers) September 2, 2021
How to Remove Outliers in R {https://t.co/IcHI3c7m1U} #rstats #DataScience
— R-bloggers (@Rbloggers) September 29, 2021
A Step-By-Step Guide To Web Scraping With R {https://t.co/hSAl6ImAp2} #rstats #DataScience
— R-bloggers (@Rbloggers) September 25, 2021
Machine Learning : Workflow {https://t.co/Ww5FmDMSaA} #rstats #DataScience
— R-bloggers (@Rbloggers) September 19, 2021
Top 10 dplyr Functions — Data Analysis Made Easy {https://t.co/kbrIxGHqLM} #rstats #DataScience
— R-bloggers (@Rbloggers) September 25, 2021
Animating Network Evolutions with gganimate {https://t.co/PnT0ItNPO2} #rstats #DataScience
— R-bloggers (@Rbloggers) September 16, 2021
Power Analysis by Data Simulation in R – Part IV {https://t.co/mYNzDfEjee} #rstats #DataScience
— R-bloggers (@Rbloggers) September 3, 2021
---
title: "RBloggers Top Tweets"
output:
flexdashboard::flex_dashboard:
vertical_layout: scroll
source_code: embed
theme:
version: 4
bootswatch: yeti
css: styles/main.css
---
```{r setup, include=FALSE}
library(flexdashboard)
library(dplyr)
library(httr)
library(lubridate)
library(jsonlite)
library(purrr)
rbloggers <- fromJSON("data/rbloggers.json")
get_tweet_embed <- function(user, status_id) {
url <-
stringr::str_glue(
"https://publish.twitter.com/oembed?url=https://twitter.com/{user}/status/{status_id}&partner=&hide_thread=false"
)
response <- GET(url) %>%
content()
return(shiny::HTML(response$html))
}
```
Column {.tabset .tabset-fade}
-----------------------------------------------------------------------
### Top Tweets - 7 days {.tweet-wall}
```{r}
rblog_7 <- rbloggers %>%
mutate(created_at = as_date(created_at)) %>%
filter(created_at %within% interval(start = today() - 7, end = today())) %>%
slice_max(favorite_count + retweet_count, n = 12)
rblog_7_html <-
map2_chr(rblog_7$screen_name, rblog_7$status_id, get_tweet_embed)
shiny::HTML(stringr::str_glue("{rblog_7_html}"))
```
### Top Tweets - 30 days {.tweet-wall}
```{r}
rblog_30 <- rbloggers %>%
mutate(created_at = as_date(created_at)) %>%
filter(created_at %within% interval(start = today() - 30, end = today())) %>%
slice_max(favorite_count + retweet_count, n = 12)
rblog_30_html <-
map2_chr(rblog_30$screen_name, rblog_30$status_id, get_tweet_embed)
shiny::HTML(stringr::str_glue("{rblog_30_html}"))
```